{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7b2cb9fb",
   "metadata": {},
   "source": [
    "# PC algorithm for time series causal discovery\n",
    "\n",
    "The Peter-Clark (PC) algorithm is one of the most general purpose algorithms for causal discovery that can be used for both tabular and time series data, of both continuous and discrete types. Briefly, the PC algorithm works in two steps, it first identifies the undirected causal graph, and then (partially) directs the edges. In the first step, we check for the existence of a causal connection between every pair of variables by checking if there exists a condition set (a subset of variables excluding the two said variables), conditioned on which, the two variables are independent. In the second step, the edges are directed by identifying colliders. Note that the edge orientation strategy of the PC algorithm may result in partially directed graphs. In the case of time series data, the additional information about the time steps associated with each variable can also be used to direct the edges.\n",
    "\n",
    "The PC algorithm makes four core assumptions: \n",
    "1. Causal Markov condition, which implies that two variables that are d-separated in a causal graph are probabilistically independent, \n",
    "2. faithfulness, i.e., no conditional independence can hold unless the Causal Markov condition is met, \n",
    "3. no hidden confounders, and \n",
    "4. no cycles in the causal graph. \n",
    "5. For time series data, it makes the additional assumption of stationarity, i.e., the properties of a. random variable is agnostic to the time step. \n",
    "\n",
    "Finally, our current implementation of PC does not support contemporaneous causal links."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "47b47f0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline     \n",
    "import pickle as pkl\n",
    "import time\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "30960522",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "\n",
    "from causalai.models.time_series.pc import PCSingle, PC\n",
    "from causalai.models.common.CI_tests.partial_correlation import PartialCorrelation\n",
    "from causalai.models.common.CI_tests.kci import KCI\n",
    "from causalai.data.data_generator import DataGenerator, GenerateRandomTimeseriesSEM\n",
    "from causalai.models.common.CI_tests.discrete_ci_tests import DiscreteCI_tests\n",
    "\n",
    "\n",
    "# also importing data object, data transform object, and prior knowledge object, and the graph plotting function\n",
    "from causalai.data.time_series import TimeSeriesData\n",
    "from causalai.data.transforms.time_series import StandardizeTransform\n",
    "from causalai.models.common.prior_knowledge import PriorKnowledge\n",
    "from causalai.misc.misc import plot_graph, get_precision_recall"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3bb7e3f",
   "metadata": {},
   "source": [
    "## Load and Visualize Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c82421d",
   "metadata": {},
   "source": [
    "Load the dataset and visualize the ground truth causal graph. For the purpose of this example, we will use a synthetic dataset available in our repository."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c3d2edc3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'0': [('5', -3), ('2', -1)],\n",
       " '1': [('2', -2)],\n",
       " '2': [('3', -4), ('0', -1)],\n",
       " '3': [('3', -4)],\n",
       " '4': [('4', -2), ('0', -3)],\n",
       " '5': [('3', -3), ('2', -4)]}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# fn = lambda x:x\n",
    "# coef = 0.1\n",
    "# sem = {\n",
    "#         'a': [], \n",
    "#         'b': [(('a', -1), coef, fn), (('f', -1), coef, fn)], \n",
    "#         'c': [(('b', -2), coef, fn), (('f', -2), coef, fn)],\n",
    "#         'd': [(('b', -4), coef, fn), (('b', -1), coef, fn), (('g', -1), coef, fn)],\n",
    "#         'e': [(('f', -1), coef, fn)], \n",
    "#         'f': [],\n",
    "#         'g': [],\n",
    "#         }\n",
    "\n",
    "T = 5000\n",
    "\n",
    "var_names = [str(i) for i in range(6)]\n",
    "sem = GenerateRandomTimeseriesSEM(var_names=var_names, max_num_parents=2, seed=1)\n",
    "\n",
    "data_array, var_names, graph_gt = DataGenerator(sem, T=T, seed=0)\n",
    "graph_gt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad7b11b5",
   "metadata": {},
   "source": [
    "Now we perform the following operations:\n",
    "1. Standardize the data arrays\n",
    "2. Create the data object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "696d4e55",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "# 1.\n",
    "StandardizeTransform_ = StandardizeTransform()\n",
    "StandardizeTransform_.fit(data_array)\n",
    "\n",
    "data_trans = StandardizeTransform_.transform(data_array)\n",
    "\n",
    "# 2.\n",
    "data_obj = TimeSeriesData(data_trans, var_names=var_names)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e99ae343",
   "metadata": {},
   "source": [
    "We visualize the data and graph below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6a1034ec",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "plot_graph(graph_gt, node_size=1000)\n",
    "\n",
    "\n",
    "\n",
    "for i, n in enumerate(var_names):\n",
    "    plt.plot(data_trans[-100:,i], label=n)\n",
    "plt.legend()\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee696c23",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "32601e85",
   "metadata": {},
   "source": [
    "## Causal Discovery (CD)\n",
    "\n",
    "Our library supports running Granger causal discovery in two modes:\n",
    "\n",
    "1. Targeted CD: Find causal parents of a single given variable. This is useful when we are only interested in finding out the cause of a specific variable, and not others. We thus save both compute and time this way.\n",
    "2. Full CD: Find the full causal graph. This is costlier and scales linearly with the number of variables compared to the time taken by the mode above.\n",
    "\n",
    "Enable/Disable Parallel Processing:\n",
    "\n",
    "When we instantiate our causal discovery model, we need to decide if we want to use multi-processing. Multi-processing typically provides a significant speed-up for the PC algorithm. In order to use multi-processing in our causal discovery library, we pass the argument use_multiprocessing=True to the model constructor. It's default value is False.\n",
    "\n",
    "When running the PC algorithm in either of the above configurations, there is an optional functionality to enable a greedy heuristic that provides a further speed-up. More details are provided below in the Greedy Heuristic section."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad42d0b4",
   "metadata": {},
   "source": [
    "### Targeted Causal Discovery"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4245c323",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target Variable: 0, using max_lag 5, pvalue_thres 0.001\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "prior_knowledge = None # PriorKnowledge(forbidden_links={'C': ['A']})\n",
    "\n",
    "target_var = '0' # 'c'\n",
    "max_lag = 5\n",
    "pvalue_thres = 0.001#0.000000001\n",
    "print(f'Target Variable: {target_var}, using max_lag {max_lag}, pvalue_thres {pvalue_thres}')\n",
    "\n",
    "CI_test = PartialCorrelation() # use KCI() if the causal relationship is expected to be non-linear\n",
    "# CI_test = KCI()\n",
    "pc_single = PCSingle(\n",
    "    data=data_obj,\n",
    "    prior_knowledge=prior_knowledge,\n",
    "    CI_test=CI_test,\n",
    "    use_multiprocessing=False\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d045c77d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time taken: 0.15s\n",
      "\n",
      "parents \n",
      " [('5', -3), ('2', -1)]\n",
      "\n",
      "value_dict \n",
      " {('0', -1): 0.008617392491692836, ('0', -2): 0.0018719655352873257, ('0', -3): -0.018247310621102835, ('0', -4): -0.008172415285694823, ('0', -5): -0.022965949303747218, ('1', -1): 0.0065014703986125445, ('1', -2): 0.0054060589346605565, ('1', -3): 0.010927859638999218, ('1', -4): 0.018428080161603726, ('1', -5): -0.004880797801728776, ('2', -1): 0.07966085711107593, ('2', -2): 0.020003191601610463, ('2', -3): -0.010856883544675107, ('2', -4): 0.005053791802773835, ('2', -5): -0.0011014065390646153, ('3', -1): 0.03805532987698295, ('3', -2): -0.019954514609284667, ('3', -3): -0.0013006743749435922, ('3', -4): 0.001083817267272737, ('3', -5): -0.00631117812741271, ('4', -1): 0.004332264603256165, ('4', -2): 0.0030765021801625668, ('4', -3): 0.022561445613761433, ('4', -4): 0.002766552799842021, ('4', -5): -0.018253328570831766, ('5', -1): -0.021362902145286, ('5', -2): 0.012457248161551112, ('5', -3): 0.10487138358725479, ('5', -4): -0.03378770240873199, ('5', -5): 0.00949296311111276}\n",
      "\n",
      "pvalue_dict \n",
      " {('0', -1): 0.5437681136635399, ('0', -2): 0.895076012354255, ('0', -3): 0.1985587454758103, ('0', -4): 0.564768268966926, ('0', -5): 0.10561669473008387, ('1', -1): 0.6469185611842226, ('1', -2): 0.7032989349892531, ('1', -3): 0.44135104324767815, ('1', -4): 0.19414737580413452, ('1', -5): 0.7309481459822311, ('2', -1): 1.8962443807433843e-08, ('2', -2): 0.15871453292040036, ('2', -3): 0.44432340441297347, ('2', -4): 0.7218011906486563, ('2', -5): 0.9381490743831484, ('3', -1): 0.0073172562883217565, ('3', -2): 0.15973075647087706, ('3', -3): 0.9269878081050825, ('3', -4): 0.9391348897986946, ('3', -5): 0.6565797527269087, ('4', -1): 0.7601996508647306, ('4', -2): 0.8284058391576121, ('4', -3): 0.11190158349255867, ('4', -4): 0.845463515470323, ('4', -5): 0.19841071860251203, ('5', -1): 0.13226409935674308, ('5', -2): 0.3801209352060546, ('5', -3): 1.2740205766545935e-13, ('5', -4): 0.017261269740706457, ('5', -5): 0.503613902301266}\n",
      "\n",
      "undirected_edges \n",
      " []\n",
      "\n"
     ]
    }
   ],
   "source": [
    "tic = time.time()\n",
    "result = pc_single.run(target_var=target_var, pvalue_thres=pvalue_thres, max_lag=max_lag, max_condition_set_size=None)\n",
    "\n",
    "toc = time.time()\n",
    "print(f'Time taken: {toc-tic:.2f}s\\n')\n",
    "\n",
    "for key in result.keys():\n",
    "    print(key, '\\n', result[key])\n",
    "    print()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5eff5dde",
   "metadata": {},
   "source": [
    "The output variable result is a dictionary with 3 keys, _parents_, _value\\_dict_ and _pvalue\\_dict_. The first one is a list of the causal parents. Each of latter ones is a dictionary, with keys equal to all possile candidates of the specified target variable. On a side note, note that if any links are specified as forbidden in prior_knowledge, they will be ignored during the computation and will not be present in result.\n",
    "\n",
    "The dictionary result['value_dict'] contains the strength of the link between the targeted variable and each of the candidate parents. The dictionary result['pvalue_dict'] contains the p-values of the said strength. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "52f7ef20",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted parents:\n",
      "[('5', -3), ('2', -1)]\n",
      "Ground truth parents:\n",
      "[('5', -3), ('2', -1)]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(f'Predicted parents:')\n",
    "parents = result['parents']\n",
    "print(parents)\n",
    "\n",
    "print(f\"Ground truth parents:\")\n",
    "print(graph_gt[target_var])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f165286",
   "metadata": {},
   "source": [
    "The way to read this Python dictionary is that $0[t]$ has parents $5[t-3]$ and $2[t-1]$."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25110a27",
   "metadata": {},
   "source": [
    "### Full Causal Discovery"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6265ffbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using max_lag 5\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "prior_knowledge = None #  PriorKnowledge(forbidden_links={})\n",
    "\n",
    "max_lag = 5\n",
    "pvalue_thres = 0.001\n",
    "print(f'Using max_lag {max_lag}')\n",
    "CI_test = PartialCorrelation()\n",
    "# CI_test = KCI(chunk_size=100) # use if the causal relationship is expected to be non-linear\n",
    "pc = PC(\n",
    "        data=data_obj,\n",
    "        prior_knowledge=prior_knowledge,\n",
    "        CI_test=CI_test,\n",
    "        use_multiprocessing=False\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "528219fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time taken: 0.73s\n",
      "\n"
     ]
    }
   ],
   "source": [
    "tic = time.time()\n",
    "\n",
    "\n",
    "result = pc.run(pvalue_thres=pvalue_thres, max_lag=max_lag)\n",
    "\n",
    "toc = time.time()\n",
    "print(f'Time taken: {toc-tic:.2f}s\\n')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b62ad272",
   "metadata": {},
   "source": [
    "The output _result_ now has the variable names as its keys, and the value corresponding to each key has the same format as the output of _pc\\_single.run()_ example above for targeted CD."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6fc53f69",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted parents:\n",
      "0: [('5', -3), ('2', -1)]\n",
      "1: [('2', -2)]\n",
      "2: [('3', -4), ('0', -1)]\n",
      "3: [('3', -4)]\n",
      "4: [('0', -3), ('4', -2)]\n",
      "5: [('2', -4), ('3', -3)]\n",
      "\n",
      "Ground truth parents:\n",
      "0: [('5', -3), ('2', -1)]\n",
      "1: [('2', -2)]\n",
      "2: [('3', -4), ('0', -1)]\n",
      "3: [('3', -4)]\n",
      "4: [('4', -2), ('0', -3)]\n",
      "5: [('3', -3), ('2', -4)]\n",
      "Precision 1.00, Recall: 1.00, F1 score: 1.00\n"
     ]
    }
   ],
   "source": [
    "print(f'Predicted parents:')\n",
    "graph_est={n:[] for n in result.keys()}\n",
    "for key in result.keys():\n",
    "    parents = result[key]['parents']\n",
    "    graph_est[key].extend(parents)\n",
    "    print(f'{key}: {parents}')\n",
    "\n",
    "print(f\"\\nGround truth parents:\")  \n",
    "for key in graph_gt.keys():\n",
    "    print(f'{key}: {graph_gt[key]}')\n",
    "\n",
    "precision, recall, f1_score = get_precision_recall(graph_est, graph_gt)\n",
    "print(f'Precision {precision:.2f}, Recall: {recall:.2f}, F1 score: {f1_score:.2f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6611c4e",
   "metadata": {},
   "source": [
    "The way to read this Python dictionary is that $0[t]$ has parents $5[t-3]$ and $2[t-1]$, and so on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e8d17df",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "5af828cd",
   "metadata": {},
   "source": [
    "## Greedy Heuristic when the underlying true causal graph is sparse\n",
    "\n",
    "When running the PC algorithm in either of the above configurations, enabling the greedy heuristic provides a speed-up on top of multi-processing.\n",
    "\n",
    "The exact algorithm can be understood by looking through the _run_greedy()_ in pc.py. In a nut shell, this procedure tries to determine the causal link between two variables by greedily conditioning on a condition set of increasing size, from 0 to the maximum number of possible parents or max_condition_set_size (whichever is lower). At each step, it permanently eliminates variables in the condition set whose causal strength is less than a specified value (determined by the pvalue_thres). Once all combinations of nodes are used as condition sets until max_condition_set_size, it then uses all the variables (except those that got eliminated, and the 2 variables being check) as the condition set. This step helps remove edges for which the condition set is larger than max_condition_set_size.\n",
    "\n",
    "Using this greedy heuristic can significantly speed-up the algorithm when the underlying true causal graph is sparse because most of the candidate parents for each variable get eliminated in the greedy step with a relatively small computational cost.\n",
    "\n",
    "An example for the single target variable case is given below. The only additional argument that needs to be passed is _max\\_condition\\_set\\_size_. The full causal discovery algorithm can be called similarly with the same additional argument _max\\_condition\\_set\\_size_.\n",
    "\n",
    "We compare the time taken by the PC algorithm with and without the greedy heuristic. To make the difference in time taken apparent, we set max_lag=30, which makes the effective number of variables = 6x30=180."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ef21d893",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target Variable: c, using max_lag 30\n"
     ]
    }
   ],
   "source": [
    "\n",
    "T = 5000\n",
    "\n",
    "var_names = ['a','b','c','d','e','f']\n",
    "sem = GenerateRandomTimeseriesSEM(var_names=var_names, max_num_parents=2, seed=1)\n",
    "\n",
    "data_array, var_names, graph_gt = DataGenerator(sem, T=T, seed=0)\n",
    "\n",
    "\n",
    "StandardizeTransform_ = StandardizeTransform()\n",
    "StandardizeTransform_.fit(data_array)\n",
    "data_trans = StandardizeTransform_.transform(data_array)\n",
    "data_obj = TimeSeriesData(data_trans, var_names=var_names)\n",
    "\n",
    "\n",
    "\n",
    "prior_knowledge = None # PriorKnowledge(forbidden_links={'b': ['c']})\n",
    "\n",
    "target_var = 'c'\n",
    "max_lag = 30\n",
    "print(f'Target Variable: {target_var}, using max_lag {max_lag}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a9ffc9dd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ground truth parents for target variable c:\n",
      "[('d', -4), ('a', -1)]\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-08-17 07:38:31,943\tINFO worker.py:1553 -- Started a local Ray instance.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time taken without greedy heuristic: 28.82s\n",
      "Predicted parents without greedy heuristic:\n",
      "[('d', -4), ('a', -1), ('c', -17)]\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-08-17 07:39:01,090\tINFO worker.py:1553 -- Started a local Ray instance.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time taken with greedy heuristic: 11.91s\n",
      "Predicted parents with greedy heuristic:\n",
      "[('d', -4), ('a', -1), ('c', -17)]\n"
     ]
    }
   ],
   "source": [
    "print(f\"Ground truth parents for target variable {target_var}:\")\n",
    "print(graph_gt[target_var])\n",
    "print('\\n')\n",
    "\n",
    "# without greedy heuristic\n",
    "\n",
    "CI_test = PartialCorrelation()\n",
    "pc_single = PCSingle(\n",
    "    data=data_obj,\n",
    "    prior_knowledge=prior_knowledge,\n",
    "    CI_test=CI_test,\n",
    "    use_multiprocessing=True\n",
    "    )\n",
    "\n",
    "tic = time.time()\n",
    "result = pc_single.run(target_var=target_var, pvalue_thres=0.01, max_lag=max_lag, max_condition_set_size=None) \n",
    "\n",
    "toc = time.time()\n",
    "print(f'Time taken without greedy heuristic: {toc-tic:.2f}s')\n",
    "print(f'Predicted parents without greedy heuristic:')\n",
    "parents = result['parents']\n",
    "print(parents)\n",
    "print('\\n')\n",
    "\n",
    "\n",
    "# with greedy heuristic\n",
    "\n",
    "CI_test = PartialCorrelation()\n",
    "pc_single = PCSingle(\n",
    "    data=data_obj,\n",
    "    prior_knowledge=prior_knowledge,\n",
    "    CI_test=CI_test,\n",
    "    use_multiprocessing=True\n",
    "    )\n",
    "\n",
    "tic = time.time()\n",
    "\n",
    "result = pc_single.run(target_var=target_var, pvalue_thres=0.01, max_lag=max_lag, max_condition_set_size=2)\n",
    "\n",
    "toc = time.time()\n",
    "print(f'Time taken with greedy heuristic: {toc-tic:.2f}s')\n",
    "print(f'Predicted parents with greedy heuristic:')\n",
    "parents = result['parents']\n",
    "print(parents)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b105b972",
   "metadata": {},
   "source": [
    "The way to read this Python dictionary is that $c[t]$ has parents $d[t-4]$ and $a[t-1]$. Note that the greedy heuristic takes less time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5c6cbb9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cce5cca8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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